Morphological component analysis and adaptive dictionary learning-based scene image text detection method

Abstract

The present invention relates to a morphological component analysis and adaptive dictionary learning-based scene image text detection method and belongs to the digital image processing technical field. The method includes the following steps that: sample data are constructed, and two initial dictionaries, namely, a text dictionary and a background dictionary, are trained; dictionaries and parse representation coefficients corresponding to the characters and background of an image to be detected are calculated through the trained initial dictionaries, the image to be detected and an adaptive dictionary learning algorithm; a text image in the image to be detected is reconstructed through an adaptive dictionary and the parse representation coefficients corresponding to the image to be detected; the reconstructed text image is processed through using a heuristic rule, so that a candidate character area in the image to be detected can be detected out; and a final text area is framed through a rectangular box. With the method of the invention adopted, a computer can automatically understand semantic information contained in the image, and strong support can be provided for blind guiding technology, license plate recognition and vehicle positioning and tracking technology, image retrieval technology and the like.

Description

technical field

[0001] The invention relates to a method for scene image character detection based on morphological component analysis and adaptive dictionary learning, belonging to the technical field of digital image processing. Background technique

[0002] Since entering the 21st century, the Internet industry has developed rapidly, coupled with the vigorous development of smart phones in recent years, the digital information on PC and mobile terminals is growing rapidly. Digital images and videos are just one of the main elements of today's digital world. Digital images and videos often contain a large number of text areas, and these text information are important clues to understand the meaning of the images and videos. How to extract text information from complex natural scene images will have extraordinary significance for image understanding and image retrieval. Therefore, the research on text positioning technology in scene images has attracted many scholars at hom...

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